From Competency to Influence: AI Training and Teachers’ Interest in AI Usage among Library and Media Teachers in School Digital Ecosystems

This study examines how AI competency and training are associated with teachers’ interest in using artificial intelligence among Library and Media Teachers within school digital ecosystems. A cross-sectional survey was conducted among secondary school teachers in Negeri Sembilan, Malaysia, using multi-item Likert scales to measure AI competency, AI training, and interest in AI usage, with all constructs demonstrating strong reliability. The findings reveal that teachers exhibit high levels of interest in AI usage alongside relatively strong competency, despite experiencing lower and more varied levels of training. Further analysis indicates that AI competency serves as a significant positive predictor of teachers’ interest, whereas AI training does not demonstrate a significant direct association when considered alongside competency. This pattern suggests that the influence of training on teachers’ interest may depend on the extent to which it contributes to competency development. The study therefore highlights a misalignment between teachers’ strong interest in AI and the current effectiveness of training approaches. By positioning competency as a key mechanism linking policy to practice, the findings underscore the strategic role of Library and Media Teachers as facilitators of AI integration within school digital ecosystems. Collectively, these findings highlight the need for more practice-oriented and competency-focused professional development to support the effective implementation of the National Digital Education Policy.

artificial intelligence in education; teacher competency; professional development; teacher interest; school digital ecosystems

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